Researchers from the Institute for Space Astrophysics and Planetology in Italy, the Czech Academy of Sciences, the University of Oslo, and the British Antarctic Survey have collaborated on a project to develop a new data product that could have significant implications for space weather applications and the energy sector. The team, led by Yaqi Jin and including Luca Spogli, Daria Kotova, Alan Wood, Jaroslav Urbář, Lucilla Alfonsi, Mainul Mohammed Hoque, and Wojciech Miloch, utilized high-resolution plasma density data from the Swarm satellites to characterize ionospheric structures and irregularities. Their findings were published in the journal Geophysical Research Letters.
The researchers analyzed eight years of data from the Swarm A satellite, focusing on the period from late 2014 to the end of 2022. They developed a set of parameters to characterize multi-scale ionospheric structures and irregularities along the satellite’s orbit. These parameters include density gradients over different window sizes, the rate of change of density index, power spectral density, and the spectral slope at both low and high latitudes. The team found that the variations of plasma structures and irregularities are dependent on solar activity, season, local time, and geomagnetic activities, with different patterns observed between low and high latitudes.
For instance, the high-latitude ionosphere is characterized by persistent ionospheric structures and irregularities poleward of 60 magnetic latitude. In contrast, low-latitude ionospheric irregularities are dominant during specific local times near the magnetic equator. The occurrence of steep spectral slope at high latitudes shows clear seasonal variations, maximizing during local summer and minimizing during local winter in both hemispheres. However, the occurrence of steep spectral slope at low latitudes is only notable when significant plasma structures and irregularities are present.
The researchers also calculated the histogram of spectral slopes at low latitudes when the rate of change of density index is enhanced. The histogram resembles a Gaussian distribution with an expected value of 1.97. The processed data are now available to the wider scientific community, providing valuable insights into the magnetosphere-ionosphere-thermosphere coupling and the near-Earth space environment.
For the energy sector, understanding ionospheric structures and irregularities is crucial for improving the accuracy of satellite-based navigation and communication systems, which are essential for the operation of renewable energy systems and smart grids. The new data product developed by this research team could help energy companies mitigate the impacts of space weather on their infrastructure, ensuring more reliable and efficient energy distribution. The research was published in Geophysical Research Letters.
This article is based on research available at arXiv.